MSA-LMC / S2D

[TAFFC 2024] The official implementation of paper: From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos

Date Created 2023-11-14 (about a year ago)

Commits 25 (last one 17 days ago)

Stargazers 55 (1 this week)

Watchers 4 (0 this week)

Forks 1

License apache-2.0

Ranking

RepositoryStats indexes 595,890 repositories, of these MSA-LMC/S2D is ranked #445,828 (25th percentile) for total stargazers, and #377,353 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #85,354/119,419.

MSA-LMC/S2D is also tagged with popular topics, for these it's ranked: transfer-learning (#244/314)

Other Information

MSA-LMC/S2D has Github issues enabled, there are 2 open issues and 12 closed issues.

Homepage URL: https://ieeexplore.ieee.org/document/10663980

All Topics

adapater image-to-video transfer-learning facial-expression-recognition dynamic-facial-expression-recognition

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25 commits on the default branch (main) since jan '22

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updated: 2024-12-21 @ 12:09pm, id: 718661629 / R_kgDOKtXn_Q